Resources and insights

Discover how self-service analytics tools are empowering non-technical users, enabling data access and insights without coding, streamlining decision-making.

Discover 8 effective ways to build data literacy across business and technical teams, breaking down barriers and enhancing collaboration for data-driven success.

Prophecy and Databricks are redefining how teams build and manage data pipelines on Databricks SQL.

Prophecy Introduces Fully Governed Data Preparation for Databricks SQL

Explore best practices and modern examples in data pipeline strategy. Learn to boost business success with scalable and reliable data solutions.

Everything you need to know to accelerate ETL modernization

We’ve written before about the challenge of having too few data engineers. There is another problem. 

Prophecy and data leaders embrace the GenAI moment at Gartner 2025

Data teams and analysts are inadvertently siloed into different parts of their organizations. These are the 5 data dysfunctions that breed this situation.

By modernizing the ETL process on Databricks, Prophecy can provide organizations with a more agile, scalable, and cost-effective solution for managing their data.

Our new survey shows that data leaders are embracing GenAI and bracing for new challenges

Join the Prophecy team in Orlando to see how genAI is reshaping data teams

Maximize productivity without the complexity.

How copilots will change data transformation, and in the process evolve beyond conversational interfaces

Prophecy brings championship winning data, critical healthcare data, and AI for data transformation to DAIS 2024

Inaugural course addresses the growing data engineering skills gap through agile, self-paced training

Struggling with data transformation? Hiring more data engineers is not the answer. Learn how low-code data transformation unlocks the full potential of your users and your data.

With the release of Prophecy 3.2, we are thrilled to announce two game-changing capabilities: Prophecy Package Builder and Prophecy Package Hub.

Discover how to build generative AI applications leveraging enterprise data. Learn to identify use cases, choose effective models, and navigate challenges with our comprehensive guide.

In this blog, we'll take a look at the differences between prompt engineering and fine-tuning, and provide insights into each approach

Companies can train small, domain-specific language models in a matter of hours or days rather than weeks or months provided they have governed and accurate training inputs. 

Stop getting stuck managing SQL files, start making progress for your business today

Build powerful gen AI applications on private enterprise data in just hours

Unlock the power of generative AI in data engineering with Prophecy’s Data Copilot.

Empowering business data users to quickly and easily build scalable data pipelines on the lakehouse

Learn how the Texas Rangers use Prophecy and Databricks Lakehouse as the foundation of their data mesh architecture to gain a competitive advantage with low-code data engineering.

Leverage Prophecy’s low-code approach and integration with dbt Core to build SQL data pipelines without compromising on engineering best practices

Discover how Prophecy 3.0 arms all data users with low-code SQL, so they can quickly and easily build scalable data pipelines, resulting in highly impactful data products.

In this blog, we learn about the concept of financial reporting, its importance, the various challenges faced while generating an efficient and reliable financial report and how Prophecy makes the complete process easy sailing.

Prophecy is delighted to announce we raised a $25M Series A led by Insight Partners, with participation from SignalFire, Dig Ventures and Berkeley SkyDeck.

In a Data Engineering Battle, Prophecy presented a complete, low-code data engineering product with a session for low-code Spark, low-code Airflow and column-level lineage that hundreds attended. Here are the poll results.

Announcing the launch of Prophecy SaaS!

The disruption is agile software practices in data engineering made usable for the many. Allow me to explain.

We're excited to share what we have built with you. Sign up and let us know what you think!

The clock strikes noon on Shadow IT

Prophecy also provides a highly automated replacement for legacy ETL products to accelerate the journey to open source and cloud computing.

Prophecy team was out in force at one of the data world’s biggest events

Accelerating data transformation with AI to deliver insights

Bringing data teams together for the holidays

Get an exciting recap from Databricks Data + AI summit including Prophecy’s announcements around low-code data engineering and generative AI app development

Prophecy’s booth will be hopping with book signings, Copilots, and the latest on data and AI

Explore alternatives to Alteryx for modern data prep. Explore options and how Prophecy delivers scalability and openness to modernize data preparation.

Discover how Prophecy revolutionizes your data operations.

Prophecy attended the CDOIQ Symposium last week in Boston.

Databricks held their annual Data+AI Summit in San Francisco last week at Moscone Center.

Learn key steps to follow, how to define the ETL pipeline using Spark APIs and dataframes, and best practices for testing and optimizing pipelines for maximum efficiency

Bringing the power of low-code data engineering to the masses

Let's get started with PySpark using a visual interface to generate open-source Spark code.

For enterprises, navigating the cloud transition can be tricky. This describes the two paradigms for ETL in the cloud, and the factors to consider when choosing one.

Just a few days ago, we announced a Prophecy for Databricks. In this blog post — Part 2 of that announcement — we dig into how Prophecy makes data engineering simple for any data practitioner on Databricks.‍

Prophecy presented a complete, low-code data engineering product at the Data + AI Summit 2021. Hundreds attended our sessions on low-code Spark, low-code Airflow and column-level lineage. Here are the results from the polls we conducted there.

Learn about the four main pillars of productive, powerful, low-code data engineering on Spark. See all the pieces in action!

We discuss the two cloud data engineering architectures and advise which one to pick as you move your ETL to the cloud.